Calibration of remotely sensed, coarse resolution NDVI to CO2 fluxes in a sagebrush–steppe ecosystem

Abstract

The net ecosystem exchange (NEE) of carbon flux can be partitioned into gross primary productivity (GPP) and respiration (R). The contribution of remote sensing and modeling holds the potential to predict these components and map them spatially and temporally. This has obvious utility to quantify carbon sink and source relationships and to identify improved land management strategies for optimizing carbon sequestration. The objective of our study was to evaluate prediction of 14-day average daytime CO 2 fluxes (F day) and nighttime CO 2 fluxes (R n) using remote sensing and other data. F day and R n were measured with a Bowen ratio-energy balance (BREB) technique in a sagebrush (Artemisia spp.)-steppe ecosystem in northeast Idaho, USA, during 1996-1999. Micrometeorological variables aggregated across 14-day periods and time-integrated Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (iNDVI) were determined during four growing seasons (1996-1999) and used to predict F day and R n. We found that iNDVI was a strong predictor of F day (R 2 = 0.79, n = 66, P < 0.0001). Inclusion of evapotranspiration in the predictive equation led to improved predictions of F day (R 2 = 0.82, n = 66, P < 0.0001). Crossvalidation indicated that regression tree predictions of F day were prone to overfitting and that linear regression models were more robust. Multiple regression and regression tree models predicted R n quite well (R 2 = 0.75-0.77, n = 66) with the regression tree model being slightly more robust in crossvalidation. Temporal mapping of F day and R n is possible with these techniques and would allow the assessment of NEE in sagebrush-steppe ecosystems. Simulations of periodic F day measurements, as might be provided by a mobile flux tower, indicated that such measurements could be used in combination with iNDVI to accurately predict F day. These periodic measurements could maximize the utility of expensive flux towers for evaluating various carbon management strategies, carbon certification, and validation and calibration of carbon flux models.

Seasonal variation in carbon dioxide exchange over a Mediterranean annual grassland in California

“…Such data are needed to validate indices that are being evaluated with reflectance data measured by instruments on satellite-based remote sensing platforms-normalized difference vegetation index (NDVI)-to upscale carbon assimilation fluxes to regional, continental and global scales (Running et al, 1999;Turner et al, 1999;Myneni et al, 2002;Wylie et al, 2003).…”

Dependence of Co2 Flux on the Key Abiotic and Biotic Parameters in Semi-Natural Grasslands Either Traditionally Grazed or Excluded From Grazing

“…Flanagan et al, 2002;Wylie et al, 2003;Gilmanov et al, 2005). The dependence of CO 2 fixation on leaf area shows positive and significant correlation (P < 0.05) in both cases (Fig.…”

“…High correlation between the actual LAI and net primer production has been observed in many cases (e.g. Gilmanov, 2005) even when including interannual differences (Wylie et al, 2003). In grasslands much of variation in NEE is constrained by amount of precipitation (Flanagan et al, 2002), however responses of the ecosystem carbon exchange to climatic factors may change according to the phenological stage (Yuste et al, 2004).…”

Remote sensing of ecosystem services: An opportunity for spatially explicit assessment

“…The NDVI, which is proved to directly relate to the land cover condition, is applied to estimating primary productivity. The possibility of predicting average primary productivity by its regression relationship with NDVI has been observed in the Arctic tundra (Boelman et al, 2003) and in steppe ecosystems (Wylie et al, 2003). NDVI tends to be saturated when biomass increases to a high value (Myneni et al, 1995;Hao et al, 2008), this being especially obvious in evergreen forest area (Rahman et al, 2001).…”